Re:A few negative online reviews early on can hurt a restaurant
by awslattery on Friday July 24, 2020 @09:36PM
(#23946177)
It's present for me as a % match to a restaurant I'm a regular at back home. Signals I have seen in this are menu item similarity, photo count by similar reviewers, and more basic metadata.
It didn't really translate well to visiting Japan, but does great when in a new metro and not having any personal recommendations to go off.
Re:A few negative online reviews early on can hurt a restaurant
by splonk on Friday July 24, 2020 @11:50PM
(#23946727)
Good to know. I remember the Tokyo team working on menu item extraction back then, hopefully they managed to make it work. I don't believe we were looking at photo count at all - probably user submitted photos weren't a feature on Maps at the time.
The cross city problem is one of the things I've looked at a lot (I actually wrote a design doc for it at a different company). Even with really good coverage in New York/San Francisco/London/Tokyo due to our teams being based there, it was hard to get significant personalized ranking improvement. Maybe it's better now that they have a lot more data.
That project never really reached its full potential for other reasons, but it turns out that even with a lot of data, it's hard to make big gains in ranking over just using the aggregate of all users. The intersection of two people's tastes is sort of surprisingly not very helpful.